kies(.../software/mySVM-www)226> mysvm examples/param.dat examples/trainreg.100.datReading examples/param.datReading examples/trainreg.100.dat   read 100 examples, dimension = 11.RSVM generatedTraining started with C = 1000..........................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................................*** ConvergenceDone training: 2009 iterations.Target function: -17.971194----------------------------------------The results are valid with an epsilon of 8.4349607e-05 on the KKT conditions.Average loss  : 8.4771035e-07 (loo-estim: 1.0221924)Avg. loss pos : 8.4349607e-05	 (1 occurences)Avg. loss neg : 8.4285601e-08	 (5 occurences)Support Vectors : 12Bounded SVs     : 0min SV: -0.53339822max SV: 0.33696135|w| = 5.9905279max |x| = 3.7772059VCdim <= 512.00184w[0] = 0.00062161486w[1] = 0.29593452w[2] = 0.5544862w[3] = 0.83351002w[4] = 1.1657402w[5] = 1.4602862w[6] = 1.7548449w[7] = 2.0309052w[8] = 2.507107w[9] = 2.8145319w[10] = 3.1454786b = 17.029053Time for learning:init        : 0soptimizer   : 1sconvergence : 0supdate ws   : 0scalc ws     : 0s=============all         : 2sSaving trained SVM to examples/trainreg.100.dat.svmmysvm ended successfully.